# Multilayer Perceptron

Use the Multilayer Perceptron (MLP) algorithm to train a set of input-output pairs to
learn to model the correlation between them. Training involves adjusting the parameters to
minimize error, and finding their correct balance to prevent model overfitting or
underfitting.

The MLP algorithm can be thought of as a deep artificial neural network. The perceptron's input layer receives the signal, and the output layer decides or predicts the input. In between the input and the output layer, there are many hidden layers that are the true computational engine that combines the basic attributes into higher-level concepts.